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Powered by Question2AnswerWhat are approaches of supervised models where the dimension of independent variables is not fixed?
https://mathsgee.com/qna/21909/what-are-approaches-of-supervised-models-where-the-dimension-of-independent-variables-is-not-fixed
In supervised models a dependent variable y is predicted from a number of features x_1, x_2, ... ,x_n . Usually n is fixed and small. An example for n=2 would be a house price y, where x_1 is the size of the property and x_2 the number of rooms.<br />
<br />
However, what are classical model approaches in case n is not fixed?<br />
<br />
An example y could be the probability y for a customer to subscribe to a new service and the x_1 , ... x_n is a list of all the previous purchases, where the length n of the list can vary greatly between individuals.<br />
This is also a common situation in natural language modelling (NLP), where a text consists of n words of varying length.<br />
What are classical approaches of the above? Those questions seem not covered much in standard courses.Data Sciencehttps://mathsgee.com/qna/21909/what-are-approaches-of-supervised-models-where-the-dimension-of-independent-variables-is-not-fixedFri, 27 Nov 2020 15:31:01 +0000What are fixed and random effects in regression?
https://mathsgee.com/qna/21908/what-are-fixed-and-random-effects-in-regression
Fixed and random effects appear in the context of regression, the analysis of variance (ANOVA) and linear models. What are the definitions and simple understandable examples of those terms? How can those concepts be understood in the context of Bayesian models?Data Sciencehttps://mathsgee.com/qna/21908/what-are-fixed-and-random-effects-in-regressionFri, 27 Nov 2020 15:11:18 +0000Answered: Which measure of centrality is least affected by outliers?
https://mathsgee.com/qna/21768/which-measure-of-centrality-is-least-affected-by-outliers?show=21818#a21818
Median will not be affected by outliers, since adding extreme terms either side will rarely change the position of the median value.Data Sciencehttps://mathsgee.com/qna/21768/which-measure-of-centrality-is-least-affected-by-outliers?show=21818#a21818Wed, 25 Nov 2020 12:06:00 +0000What are the rules of d-separation in a causal DAG?
https://mathsgee.com/qna/21644/what-are-the-rules-of-d-separation-in-a-causal-dag
What are the rules of d-separation in a causal DAG?Data Sciencehttps://mathsgee.com/qna/21644/what-are-the-rules-of-d-separation-in-a-causal-dagMon, 23 Nov 2020 08:26:06 +0000What is the purpose of randomization in clinical trials?
https://mathsgee.com/qna/21640/what-is-the-purpose-of-randomization-in-clinical-trials
What is the purpose of randomization in clinical trials?Data Sciencehttps://mathsgee.com/qna/21640/what-is-the-purpose-of-randomization-in-clinical-trialsSun, 22 Nov 2020 01:39:24 +0000What is the probability that an automobile owner purchases neither collision nor disability coverage?
https://mathsgee.com/qna/21614/what-is-the-probability-that-an-automobile-owner-purchases-neither-collision-nor-disability-coverage
An actuary studying the insurance preferences of automobile owners makes the following conclusions: (i) An automobile owner is twice as likely to purchase collision coverage as disability coverage. (ii) The event that an automobile owner purchases collision coverage is independent of the event that he or she purchases disability coverage. (iii) The probability that an automobile owner purchases both collision and disability coverages is 0.15. What is the probability that an automobile owner purchases neither collision nor disability coverage?Data Sciencehttps://mathsgee.com/qna/21614/what-is-the-probability-that-an-automobile-owner-purchases-neither-collision-nor-disability-coverageSat, 21 Nov 2020 06:25:19 +0000Calculate the probability that neither accident is severe and at most one is moderate.
https://mathsgee.com/qna/21613/calculate-the-probability-that-neither-accident-is-severe-and-at-most-one-is-moderate
Workplace accidents are categorized into three groups: minor, moderate, severe. The probability that a given accident is minor is 0.5, that it is moderate is 0.4, and that it is severe is 0.1. Two accidents occur independently in one month. Calculate the probability that neither accident is severe and at most one is moderate.Data Sciencehttps://mathsgee.com/qna/21613/calculate-the-probability-that-neither-accident-is-severe-and-at-most-one-is-moderateSat, 21 Nov 2020 06:23:48 +0000You are given P(A ∪ B) = 0.7 and P(A ∪ B' ) = 0.9. Determine P(A).
https://mathsgee.com/qna/21612/you-are-given-p-a-b-0-7-and-p-a-b-0-9-determine-p-a
You are given P(A ∪ B) = 0.7 and P(A ∪ B' ) = 0.9. Determine P(A).Data Sciencehttps://mathsgee.com/qna/21612/you-are-given-p-a-b-0-7-and-p-a-b-0-9-determine-p-aSat, 21 Nov 2020 06:22:34 +0000Determine the probability that a visit to a PCP’s office results in both lab work and referral to a specialist.
https://mathsgee.com/qna/21611/determine-the-probability-that-a-visit-to-a-pcps-office-results-in-both-lab-work-and-referral-to-a-specialist
The probability that a visit to a primary care physician’s (PCP) office results in neither lab work nor referral to a specialist is 35%. Of those coming to a PCP’s office, 30% are referred to specialists and 40% require lab work. Determine the probability that a visit to a PCP’s office results in both lab work and referral to a specialist.Data Sciencehttps://mathsgee.com/qna/21611/determine-the-probability-that-a-visit-to-a-pcps-office-results-in-both-lab-work-and-referral-to-a-specialistSat, 21 Nov 2020 06:21:48 +0000Calculate the probability that a person chosen at random owns an automobile or a house, but not both.
https://mathsgee.com/qna/21610/calculate-the-probability-that-a-person-chosen-at-random-owns-an-automobile-or-a-house-but-not-both
A marketing survey indicates that 60\% of the population owns an automobile, 30\% owns a house, and 20\% owns both an automobile and a house. Calculate the probability that a person chosen at random owns an automobile or a house, but not both.Data Sciencehttps://mathsgee.com/qna/21610/calculate-the-probability-that-a-person-chosen-at-random-owns-an-automobile-or-a-house-but-not-bothSat, 21 Nov 2020 06:20:38 +0000Given that a policyholder has died, what is the probability that the policyholder was a smoker?
https://mathsgee.com/qna/21605/given-that-a-policyholder-has-died-what-is-the-probability-that-the-policyholder-was-a-smoker
Ten percent of a company’s life insurance policyholders are smokers. The rest are nonsmokers. For each nonsmoker, the probability of dying during the year is 0.01. For each smoker, the probability of dying during the year is 0.05. Given that a policyholder has died, what is the probability that the policyholder was a smoker?Data Sciencehttps://mathsgee.com/qna/21605/given-that-a-policyholder-has-died-what-is-the-probability-that-the-policyholder-was-a-smokerFri, 20 Nov 2020 07:13:35 +0000When working with Bayesian Networks, how do you find the probabilities in the conditional probability tables?
https://mathsgee.com/qna/21582/when-working-with-bayesian-networks-how-do-you-find-the-probabilities-in-the-conditional-probability-tables
When working with Bayesian Networks, how do you find the probabilities in the conditional probability tables?Data Sciencehttps://mathsgee.com/qna/21582/when-working-with-bayesian-networks-how-do-you-find-the-probabilities-in-the-conditional-probability-tablesWed, 18 Nov 2020 06:28:33 +0000Answered: If the probability of death from a risky activity is 1% If you carry out that activity 200 times, what is the probability of death?
https://mathsgee.com/qna/21571/if-the-probability-of-death-from-a-risky-activity-is-1-if-you-carry-out-that-activity-200-times-what-is-the-probability-of-death?show=21572#a21572
<p>It is tempting to treat this like it is a Bernoulli experiment repeated 200 times resulting in a Binomial distribution as given below:</p>
<p>Answer:</p>
<p>$$1- (0.99)^{200} = 86.7\%$$</p>
<p>You are almost guaranteed of DEATH. Be careful about the risky things we do in life, including driving at high speed.</p>
<p>I disagree with this answer by Prof Arthur Mutambara on his <a rel="nofollow" href="https://www.linkedin.com/posts/arthurmutambara_if-the-probability-of-death-from-a-risky-activity-6733632618421616640-Lppy"><strong>LinkedIn.</strong></a> Here is my thinking.</p>
<p>1. The question requires the use of conditional problem given the way it is worded. Without loss of meaning, the same question can be written as follows:</p>
<p><strong>Given that it is a risky activity, the probability of death is $1\%$. If you carry out that activity 200 times, what is the probability of death?</strong></p>
<p>Using Bayes Theorem:</p>
<p>$$P(D|R) = \dfrac{P(R|D) \times P(D)}{P(R)}$$</p>
<p>Where</p>
<p>$P(D)$ is the probability of death each time (what we are trying to establish)</p>
<p>$P(R)$ is the risk rate (e.g. associated risk of being on the road)</p>
<p>$P(D|R)$ is the probability of death given that it was a risky activity</p>
<p>$P(R|D) is the risk given death</p>
<p>From the question $P(D|R) = 0.01$</p>
<p>From the <strong><a rel="nofollow" href="https://www.uneca.org/stories/un-rolls-out-zimbabwe-road-safety-performance-review-bid-reduce-carnage">UNECA website</a></strong> $P(R|D) =\dfrac{26.6}{100000}$ in Africa.</p>
<p>From intuition, $P(R)=0.99$ implying that the risk on the roads is high.</p>
<p>Substituting in Bayes Theorem:</p>
<p>$$0.01 = \dfrac{\dfrac{26.6}{100000} \times P(D)}{0.99}$$</p>
<p>Therefore $P(D) = 37.22\%$ everytime someone engages with the risky activity of travelling on some African road.</p>
<p>The 200 events are independent thus the only metric that matters is the probability of each individual outing.</p>
<p> </p>
<p> </p>
<p> </p>Data Sciencehttps://mathsgee.com/qna/21571/if-the-probability-of-death-from-a-risky-activity-is-1-if-you-carry-out-that-activity-200-times-what-is-the-probability-of-death?show=21572#a21572Tue, 17 Nov 2020 06:24:15 +0000Why Is Causal Inference Necessary?
https://mathsgee.com/qna/21566/why-is-causal-inference-necessary
Why Is Causal Inference Necessary?Data Sciencehttps://mathsgee.com/qna/21566/why-is-causal-inference-necessaryMon, 16 Nov 2020 07:57:21 +0000Answered: What are robustness checks when doing causal inference?
https://mathsgee.com/qna/21562/what-are-robustness-checks-when-doing-causal-inference?show=21563#a21563
<p>Robustness means clearly stating assumptions your methods and data rely on, and gradually relaxing each of them to see if your results still hold. It acts as an efficient coherence check if you realize your findings can dramatically change due to a single variable, especially if that variable is subject to noise, error measurement, etc.</p>
<p>Direct Acyclic Graphs (DAGs) are a great tool for checking robustness. They help you clearly spell out assumptions and hypotheses in the context of causal inference. </p>
<p><a rel="nofollow" href="http://www.dagitty.net/" target="_blank">Dagitty</a>, is a handy browser-based tool. In a nutshell, when you draw an assumed chain of causal events in Dagitty, it provides you with robustness checks on your data, like certain conditional correlations that should vanish. </p>Data Sciencehttps://mathsgee.com/qna/21562/what-are-robustness-checks-when-doing-causal-inference?show=21563#a21563Mon, 16 Nov 2020 05:20:43 +0000Answered: When is it appropriate to make a counterfactual causal estimation?
https://mathsgee.com/qna/21560/when-is-it-appropriate-to-make-a-counterfactual-causal-estimation?show=21561#a21561
<p>A classic example in tech is estimating the effect of a new feature that was released to all the user base at once: no A/B test was done and there’s absolutely no one that could be the control group. In this case, you can try making a counterfactual estimation.</p>
<p>The idea behind counterfactual estimation is to create a model that allows you to compute a <em>counterfactual</em> control group. In other words, you estimate what would happen had this feature not existed. It isn’t always simple to compute an estimate. However, if you have a model of your users that you’re confident about, then you have enough material to start doing counterfactual causal analyses!</p>
<p>Below is an e<em>xample of time series counterfactual vs. observed data by Shopify</em></p>
<p><img alt="" src="https://mathsgee.com/qna/?qa=blob&qa_blobid=9581918691447709996" style="height:380px; width:600px"></p>Data Sciencehttps://mathsgee.com/qna/21560/when-is-it-appropriate-to-make-a-counterfactual-causal-estimation?show=21561#a21561Mon, 16 Nov 2020 05:15:46 +0000Answered: How does one use difference in difference method for causal inference?
https://mathsgee.com/qna/21558/how-does-one-use-difference-in-difference-method-for-causal-inference?show=21559#a21559
<p><img alt="" src="https://mathsgee.com/qna/?qa=blob&qa_blobid=5850232941313224390" style="height:326px; width:600px"></p>
<p> </p>
<p>For this method to be applicable, you have to find a control group that shows a trend that’s parallel to your treatment group for the metric of interest, prior to any treatment being applied. Then, after treatment happens, you assume the break in the parallel trend is only due to the treatment itself. This is summed up in the above diagram.</p>Data Sciencehttps://mathsgee.com/qna/21558/how-does-one-use-difference-in-difference-method-for-causal-inference?show=21559#a21559Mon, 16 Nov 2020 05:10:04 +0000Answered: Can linear regression with fixed effects be used as a good estimator of causal effects?
https://mathsgee.com/qna/21556/can-linear-regression-with-fixed-effects-be-used-as-a-good-estimator-of-causal-effects?show=21557#a21557
In this method, the assumption is that you have collected data on all factors that divide individuals between treatment and control group. If that is true, then a simple linear regression on the metric of interest, controlling for these factors, gives a good estimate of the causal effect of being in the treatment group.Data Sciencehttps://mathsgee.com/qna/21556/can-linear-regression-with-fixed-effects-be-used-as-a-good-estimator-of-causal-effects?show=21557#a21557Mon, 16 Nov 2020 05:06:52 +0000Answered: Why are A/B test experiments impossible at times?
https://mathsgee.com/qna/21554/why-are-a-b-test-experiments-impossible-at-times?show=21555#a21555
<p>Sometimes it’s just not possible to set up an experiment. Here are a few reasons why A/B tests won’t work in every situation:</p>
<ul>
<li>Lack of tooling. For example, if your code can’t be modified in certain parts of the product.</li>
<li>Lack of time to implement the experiment.</li>
<li>Ethical concerns for example, at an e-commerce company like Shopify, randomly leaving some merchants out of a new feature that could help them with their business is sometimes not an option).</li>
<li>Just plain oversight (for example, a request to study the data from a launch that happened in the past).</li>
</ul>
<p>Fortunately, if you find yourself in one of the above situations, there are methods that exist which enable you to obtain causal estimates.</p>
<p>A quasi-experiment is an experiment where your treatment and control group are divided by a natural process that isn’t <em>truly</em> random, but are considered close enough to compute estimates. Quasi-experiments frequently occur in product companies, for example, when a feature rollout happens at different dates in different countries, or if eligibility for a new feature is dependent on the behaviour of other features (like in the case of a deprecation). In order to compute causal estimates when the control group is divided using a non-random criterion, you’ll use different methods that correspond to different assumptions on how “close” you are to the random situation.</p>Data Sciencehttps://mathsgee.com/qna/21554/why-are-a-b-test-experiments-impossible-at-times?show=21555#a21555Mon, 16 Nov 2020 05:00:15 +0000Answered: What does one need in order to start A\B Testing?
https://mathsgee.com/qna/21552/what-does-one-need-in-order-to-start-a-b-testing?show=21553#a21553
<p>Setting up an A/B test for products is a lot of work. If you’re starting from scratch, you’ll need</p>
<ul>
<li>A way to randomly assign units to the right group as they use your product.</li>
<li>A tracking mechanism to collect the data for all relevant metrics.</li>
<li>To analyze these metrics and their associated statistics to compute effect sizes and validate the causal effects you suspect.</li>
</ul>Data Sciencehttps://mathsgee.com/qna/21552/what-does-one-need-in-order-to-start-a-b-testing?show=21553#a21553Mon, 16 Nov 2020 04:50:50 +0000Which case studies show how causal insights were used validate/invalidate entire business strategies?
https://mathsgee.com/qna/21551/which-case-studies-show-how-causal-insights-were-used-validate-invalidate-entire-business-strategies
Which case studies show how causal insights were used validate/invalidate entire business strategies?Data Sciencehttps://mathsgee.com/qna/21551/which-case-studies-show-how-causal-insights-were-used-validate-invalidate-entire-business-strategiesMon, 16 Nov 2020 04:46:14 +0000How can understanding and capturing causality unlock business value for organizations?
https://mathsgee.com/qna/21550/how-can-understanding-and-capturing-causality-unlock-business-value-for-organizations
How can understanding and capturing causality unlock business value for organizations?Data Sciencehttps://mathsgee.com/qna/21550/how-can-understanding-and-capturing-causality-unlock-business-value-for-organizationsMon, 16 Nov 2020 04:44:35 +0000Which companies are using quasi-experiments and counterfactuals to build great products?
https://mathsgee.com/qna/21549/which-companies-are-using-quasi-experiments-and-counterfactuals-to-build-great-products
Which companies are using quasi-experiments and counterfactuals to build great products?Data Sciencehttps://mathsgee.com/qna/21549/which-companies-are-using-quasi-experiments-and-counterfactuals-to-build-great-productsMon, 16 Nov 2020 04:43:00 +0000What is Invariant Causal Prediction?
https://mathsgee.com/qna/21547/what-is-invariant-causal-prediction
What is Invariant Causal Prediction?Data Sciencehttps://mathsgee.com/qna/21547/what-is-invariant-causal-predictionSun, 15 Nov 2020 22:15:31 +0000WHat is the difference between the Structural Hamming Distance (SHD) and the Structural Intervention Distance (SID) for two DAGs?
https://mathsgee.com/qna/21546/what-is-the-difference-between-the-structural-hamming-distance-shd-and-the-structural-intervention-distance-sid-for-two-dags
WHat is the difference between the Structural Hamming Distance (SHD) and the Structural Intervention Distance (SID) for two DAGs?Data Sciencehttps://mathsgee.com/qna/21546/what-is-the-difference-between-the-structural-hamming-distance-shd-and-the-structural-intervention-distance-sid-for-two-dagsSun, 15 Nov 2020 22:07:37 +0000How does one compute the Structural Hamming Distance (SHD) between two DAGs?
https://mathsgee.com/qna/21545/how-does-one-compute-the-structural-hamming-distance-shd-between-two-dags
How does one compute the Structural Hamming Distance (SHD) between two DAGs?Data Sciencehttps://mathsgee.com/qna/21545/how-does-one-compute-the-structural-hamming-distance-shd-between-two-dagsSun, 15 Nov 2020 22:05:52 +0000When are graphs markov equivalent?
https://mathsgee.com/qna/21541/when-are-graphs-markov-equivalent
When are graphs markov equivalent?Data Sciencehttps://mathsgee.com/qna/21541/when-are-graphs-markov-equivalentSun, 15 Nov 2020 06:17:53 +0000What does the Reichenbach's common cause principle state?
https://mathsgee.com/qna/21540/what-does-the-reichenbachs-common-cause-principle-state
What does the Reichenbach's common cause principle state?Data Sciencehttps://mathsgee.com/qna/21540/what-does-the-reichenbachs-common-cause-principle-stateSun, 15 Nov 2020 05:34:02 +0000Do counterfactuals correspond to do-statements in the new structural model, $(S, P^{N|X=x})$?
https://mathsgee.com/qna/21539/do-counterfactuals-correspond-to-do-statements-in-the-new-structural-model-s-p-n-x-x
Given the (SCM), structural causal model, $(S, P^{N})$,a counterfactual SCM is obtained from a given observation X=x by conditioning the noise distribution to get $(S, P^{N|X=x})$. Do counterfactuals correspond to do-statements in the new structural model?Data Sciencehttps://mathsgee.com/qna/21539/do-counterfactuals-correspond-to-do-statements-in-the-new-structural-model-s-p-n-x-xSun, 15 Nov 2020 04:56:07 +0000Is the Instrument Variable always a parent or ancestor of the treatment variable?
https://mathsgee.com/qna/21538/is-the-instrument-variable-always-a-parent-or-ancestor-of-the-treatment-variable
Is the Instrument Variable always a parent or ancestor of the treatment variable?Data Sciencehttps://mathsgee.com/qna/21538/is-the-instrument-variable-always-a-parent-or-ancestor-of-the-treatment-variableSun, 15 Nov 2020 04:31:29 +0000What is the faithfulness assumption in causal modelling?
https://mathsgee.com/qna/21537/what-is-the-faithfulness-assumption-in-causal-modelling
What is the faithfulness assumption in causal modelling?Data Sciencehttps://mathsgee.com/qna/21537/what-is-the-faithfulness-assumption-in-causal-modellingSun, 15 Nov 2020 04:23:16 +0000How does one come up with the DAG for a structural causal model from observational data?
https://mathsgee.com/qna/21536/how-does-one-come-up-with-the-dag-for-a-structural-causal-model-from-observational-data
How does one come up with the DAG for a structural causal model from observational data?Data Sciencehttps://mathsgee.com/qna/21536/how-does-one-come-up-with-the-dag-for-a-structural-causal-model-from-observational-dataSun, 15 Nov 2020 04:14:32 +0000Does the falsifiability of causality and the fact that it is the arrow of time relegate the theory of the "Block Universe" to the scientific dustbin?
https://mathsgee.com/qna/21535/does-the-falsifiability-of-causality-and-the-fact-that-it-is-the-arrow-of-time-relegate-the-theory-of-the-block-universe-to-the-scientific-dustbin
Does the falsifiability of causality and the fact that it is the arrow of time relegate the theory of the "Block Universe" to the scientific dustbin?Data Sciencehttps://mathsgee.com/qna/21535/does-the-falsifiability-of-causality-and-the-fact-that-it-is-the-arrow-of-time-relegate-the-theory-of-the-block-universe-to-the-scientific-dustbinSun, 15 Nov 2020 04:07:23 +0000Are causal models falsifiable?
https://mathsgee.com/qna/21534/are-causal-models-falsifiable
Are causal models falsifiable?Data Sciencehttps://mathsgee.com/qna/21534/are-causal-models-falsifiableSun, 15 Nov 2020 03:57:47 +0000Under what circumstances are two causal models probabilistically/interventionally equivalent?
https://mathsgee.com/qna/21533/under-what-circumstances-are-two-causal-models-probabilistically-interventionally-equivalent
Under what circumstances are two causal models probabilistically/interventionally equivalent?Data Sciencehttps://mathsgee.com/qna/21533/under-what-circumstances-are-two-causal-models-probabilistically-interventionally-equivalentSun, 15 Nov 2020 03:54:33 +0000Is the statement P[R | do(X=x)] = P(R | X=x) valid with respect to randomized experiments?
https://mathsgee.com/qna/21532/is-the-statement-p-r-do-x-x-p-r-x-x-valid-with-respect-to-randomized-experiments
Is the statement P[R | do(X=x)] = P(R | X=x) valid with respect to randomized experiments?Data Sciencehttps://mathsgee.com/qna/21532/is-the-statement-p-r-do-x-x-p-r-x-x-valid-with-respect-to-randomized-experimentsSun, 15 Nov 2020 03:49:10 +0000Is it true that if you condition on the parents of the treatment, you automatically block all backdoor paths to the outcome?
https://mathsgee.com/qna/21531/is-it-true-that-if-you-condition-on-the-parents-of-the-treatment-you-automatically-block-all-backdoor-paths-to-the-outcome
Is it true that if you condition on the parents of the treatment, you automatically block all backdoor paths to the outcome?Data Sciencehttps://mathsgee.com/qna/21531/is-it-true-that-if-you-condition-on-the-parents-of-the-treatment-you-automatically-block-all-backdoor-paths-to-the-outcomeSun, 15 Nov 2020 03:27:45 +0000Does a big difference between P(Y) and P[Y | do(X=x)] imply that X has a strong causal effect on Y?
https://mathsgee.com/qna/21530/does-a-big-difference-between-p-y-and-p-y-do-x-x-imply-that-x-has-a-strong-causal-effect-on-y
Does a big difference between P(Y) and P[Y | do(X=x)] imply that X has a strong causal effect on Y?Data Sciencehttps://mathsgee.com/qna/21530/does-a-big-difference-between-p-y-and-p-y-do-x-x-imply-that-x-has-a-strong-causal-effect-on-ySun, 15 Nov 2020 03:16:20 +0000In causal inference, how is conditioning different from intervening?
https://mathsgee.com/qna/21529/in-causal-inference-how-is-conditioning-different-from-intervening
In causal inference, how is conditioning different from intervening?Data Sciencehttps://mathsgee.com/qna/21529/in-causal-inference-how-is-conditioning-different-from-interveningSun, 15 Nov 2020 03:07:13 +0000What does it mean to say, "causal models offer a stability guarantee"?
https://mathsgee.com/qna/21528/what-does-it-mean-to-say-causal-models-offer-a-stability-guarantee
What does it mean to say, "causal models offer a stability guarantee"?Data Sciencehttps://mathsgee.com/qna/21528/what-does-it-mean-to-say-causal-models-offer-a-stability-guaranteeSun, 15 Nov 2020 02:22:10 +0000In set theory what is the difference between the OR and the Exclusive OR?
https://mathsgee.com/qna/21527/in-set-theory-what-is-the-difference-between-the-or-and-the-exclusive-or
In set theory what is the difference between the OR and the Exclusive OR?Data Sciencehttps://mathsgee.com/qna/21527/in-set-theory-what-is-the-difference-between-the-or-and-the-exclusive-orSun, 15 Nov 2020 02:20:58 +0000In probability what is an event with respect to sample spaces?
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https://mathsgee.com/qna/21519/how-does-a-machine-learning-researcher-know-the-difference-between-local-and-global-minima
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